Agile Simulation of Stochastic Computing Image Processing With Contingency Tables

Sercan Aygun; M. Hassan Najafi; Mohsen Imani; Ece Olcay Gunes

doi:10.1109/TCAD.2023.3243136

Agile Simulation of Stochastic Computing Image Processing With Contingency Tables

Sercan Aygun^*
, M. Hassan Najafi
, Mohsen Imani
, Ece Olcay Gunes

^*Corresponding author for this work

Department of Electronics and Communication Engineering

Istanbul Technical University
University of Louisiana at Lafayette
University of California at Irvine

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using actual stochastic bit-streams. The proposed approach underlines the validity of CT simulation with 1) image compositing; 2) pattern detection; and 3) bilinear interpolation case studies. Using the corresponding error models, we emulate the state-of-the-art pseudo-random and quasi-random bit-streams. Experimental results show that the proposed approach achieves similar computation accuracy to the traditional SC simulation while performing runtime- and memory-efficient computations. The execution time reduces more than 200× for the image compositing task when emulating random bit-streams with CT. Pattern detection and bilinear interpolation further showed 76×and 22× lower memory usage, respectively, when employing CT.

Original language	English
Pages (from-to)	3474-3478
Number of pages	5
Journal	IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume	42
Issue number	10
DOIs	https://doi.org/10.1109/TCAD.2023.3243136
Publication status	Published - 1 Oct 2023

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Funding

This work was supported in part by the National Science Foundation (NSF) under Grant 2127780 and Grant 2019511; by the SRC Global Research Collaboration, AIHW and HW Security; by the Department of the Navy, Office of Naval Research under Grant N00014-21-1-2225 and Grant N00014- 22-1-2067; by the Air Force Office of Scientific Research under Grant 22RT0060; and by the Louisiana Board of Regents Support Fund under Grant LEQSF(2020-23)-RD-A-26, and generous gifts from Cisco, Xilinx, and Nvidia. This article was recommended by Associate Editor L. Amaru

Funders	Funder number
Louisiana Board of Regents Support Fund	LEQSF(2020-23)-RD-A-26
National Science Foundation	2019511, 2127780
Office of Naval Research	N00014- 22-1-2067, N00014-21-1-2225
Air Force Office of Scientific Research	22RT0060
U.S. Navy

Keywords

Computer-aided simulation
contingency table (CT)
image processing
stochastic computing (SC)

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10.1109/TCAD.2023.3243136

Cite this

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title = "Agile Simulation of Stochastic Computing Image Processing With Contingency Tables",

abstract = "The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using actual stochastic bit-streams. The proposed approach underlines the validity of CT simulation with 1) image compositing; 2) pattern detection; and 3) bilinear interpolation case studies. Using the corresponding error models, we emulate the state-of-the-art pseudo-random and quasi-random bit-streams. Experimental results show that the proposed approach achieves similar computation accuracy to the traditional SC simulation while performing runtime- and memory-efficient computations. The execution time reduces more than 200× for the image compositing task when emulating random bit-streams with CT. Pattern detection and bilinear interpolation further showed 76×and 22× lower memory usage, respectively, when employing CT.",

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AU - Imani, Mohsen

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PY - 2023/10/1

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N2 - The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using actual stochastic bit-streams. The proposed approach underlines the validity of CT simulation with 1) image compositing; 2) pattern detection; and 3) bilinear interpolation case studies. Using the corresponding error models, we emulate the state-of-the-art pseudo-random and quasi-random bit-streams. Experimental results show that the proposed approach achieves similar computation accuracy to the traditional SC simulation while performing runtime- and memory-efficient computations. The execution time reduces more than 200× for the image compositing task when emulating random bit-streams with CT. Pattern detection and bilinear interpolation further showed 76×and 22× lower memory usage, respectively, when employing CT.

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Agile Simulation of Stochastic Computing Image Processing With Contingency Tables

Abstract

Bibliographical note

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Keywords

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